The present invention relates generally to discrete pixel detectors, such as those used in digital x-ray imaging systems. More particularly, the invention relates to a technique for replacement of information for defective pixels in a panel to provide useful image data for processing and reconstruction.
Discrete pixel imaging systems, such as digital x-ray imaging systems, are becoming increasingly widespread for producing digital data which can be reconstructed into useful images. In current digital x-ray imaging systems, radiation from a source is directed toward a subject, typically a patient in a medical diagnostic application. A portion of the radiation passes through the patient and impacts a detector. The surface of the detector converts the radiation to light photons which are sensed. The detector is divided into a matrix of discrete picture elements or pixels, and encodes output signals based upon the quantity or intensity of the radiation impacting each pixel region. Because the radiation intensity is altered as the radiation passes through the patient, the images reconstructed based upon the output signals provide a projection of the patient""s tissues similar to those available through conventional photographic film techniques.
Digital x-ray imaging systems are particularly useful due to their ability to collect digital data which can be reconstructed into the images required by radiologists and diagnosing physicians, and stored digitally or archived until needed. In conventional film-based radiography techniques, actual films were prepared, exposed, developed and stored for use by the radiologist. While the films provide an excellent diagnostic tool, particularly due to their ability to capture significant anatomical detail, they are inherently difficult to transmit between locations, such as from an imaging facility or department to various physician locations. The digital data produced by direct digital x-ray systems, on the other hand, can be processed and enhanced, stored, transmitted via networks, and used to reconstruct images which can be displayed on monitors and other soft copy displays at any desired location.
In discrete pixel imaging detectors, such as those used in digital x-ray systems, it is not uncommon for detector output levels to vary between pixels, even when the pixels are exposed to equal levels of radiation. Such variations may be due to tolerances within the sensitivity of the detector itself, as well as to various forms of noise which may occur in the detection system. Similar differences may originate in the normal variations in the structures and performance of the circuitry associated with the individual pixels. However, while certain normal variations may be permitted, significant differences in pixel-to-pixel output from the detector are not desirable.
Such pixel-to-pixel output variations may involve both underactive pixels (i.e., those regions producing a signal significantly lower than other regions for the same received radiation) and overactive pixels (i.e., regions producing output levels significantly higher than other regions for the same received radiation). In addition to producing erroneous dark or light artifacts in the resulting image, data from such underactive or overactive pixels can adversely affect signal processing operations performed on the image, such as adjustment of contrast and tone, as well as errors in dynamic range detection and image enhancement.
Defects in pixels in solid state detectors may result from various causes. For example, high leakage currents, open circuits and short circuits can cause pixels erroneously to output signals when no significant radiation levels have impacted their locations, or to output abnormally low signal levels when radiation has impacted the pixels. It would be useful, therefore, to identify potentially defective detector pixels so as to avoid erroneous data in discrete pixel images produced from the detector output. Where significant output differences are detected between pixels of a detector, it may be useful to flag such pixels as defective, and to manage information they provide in a special manner, or simply to disregard their output.
Various approaches have been proposed for handling information voids left by defective pixels in such situations. For example, rather than simply omitting information at the defective pixel locations in the reconstructed image, certain processing techniques provide for filling the information voids with an average value of neighboring pixels. However, such techniques do not preserve the statistical integrity (e.g. characterizing noise) of the image data, and may therefore skew analyses performed on the data, such as for subsequent filtering and image processing and enhancement.
There is a need, therefore, for an improved technique for addressing information voids caused by defective pixels or aberrant pixel values in digital imaging systems. There is a particular need for a system which would allow useful images to be produced without altering the overall statistical characteristics of the image data.
The present technique provides a novel approach to pixel value substitution designed to respond to such needs. The technique may be employed in new systems or software packages configured to process digital image data, and may also be retrofitted to existing systems to enhance image quality. The approach provides values for missing or aberrant data, such as might result from one or more defective pixel circuits in a detector or detector data processing modules. The technique is particularly well suited to digital x-ray imaging systems, but may be applied in a wide range of fields where aberrant pixel data can be recognized and where replacement values may be useful in providing a more meaningful set of image data.
The technique preserves the statistical nature of the image data while offering the replacement values desired for defective pixels. In general, a base value for missing or aberrant pixel data is computed, such as by reference to other pixels in a row, column or neighborhood. Statistical characteristics of the image data are computed, such as a standard deviation value. The statistical characteristics may be reflective of noise in the image data or in a portion of the image data. A value preserving the statistical characteristics is used to complement the base value, thereby preserving the characteristics in the replacement value.